The first in a new series of Congressional Research Service reports on homeland security intelligence presents a broad introduction to the subject.
“The proliferation of intelligence and information fusion centers across the country indicate that state and local leaders believe there is value to centralizing intelligence gathering and analysis in a manner that assists them in preventing and responding to local manifestations of terrorist threats to their people, infrastructure, and other assets,” the CRS report suggests.
See “Homeland Security Intelligence: Perceptions, Statutory Definitions, and Approaches,” August 18, 2006.
Americans are paying too much for almost everything, because the United States has long treated its trucking industry as an artifact to be preserved rather than as an opportunity for innovation.
These ideas aim to advance the detailed policy solutions needed to foster public trust and implement fairness in the adoption of AI across diverse domains, from healthcare and government benefits to rural access, education, and worker protections.
The evidence is clear: algorithmic pay-setting is established in app-based work, and payroll/timekeeping failures show how software can produce systemic wage harm at scale
While a few states have taken steps to implement decision-making mechanisms for certain AI systems, too many leaders are simply accepting narratives about AI’s purported public benefit at face value – jumping to the “how” of AI implementation before thoroughly vetting potential systems and deciding whether they are appropriate to use at all.